Choosing Immune Suppression in Renal Transplantation by Efficacy and Morbidity

根据疗效和发病率选择肾移植中的免疫抑制

基本信息

批准号：
8913168
负责人：
Vikas R. Dharnidharka
金额：
$ 33.21万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-08-18 至 2019-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8913168
关键词：
Acute African American Allografting Car Phone Caucasians Cessation of life Characteristics Clinical Communication Tools Comorbidity Data Data Linkages Data Set Databases Decision Making Diabetes Mellitus Dialysis procedure Dose Drug Combinations Environment Equilibrium Evaluation Event Food and Drug Administration Drug Approval Graft Survival Health Immunologics Immunosuppression Immunosuppressive Agents Incidence Infection Institutes Internet Kidney Failure Kidney Transplantation Lead Link Lymphoma Maintenance Malignant Neoplasms Measures Medical Medicare Medicare claim Modeling Morbidity - disease rate Mycophenolate Organ Organ Donor Organ Procurements Organ Transplantation Outcome Outcomes Research Patient risk Patients Pharmaceutical Preparations Pharmacy facility Physicians Pneumonia Pregnancy Probability Procedures Protocols documentation Race Randomized Controlled Trials Regimen Registries Relative (related person)Reporting Research Resources Risk Safety Sepsis Specialist Staging Subgroup Survival Rate Tacrolimus Time Toxic effect Transplant Recipients Transplantation Update Urinary tract infection Weight base blind cohort cost cost effective cost effectiveness data registry design dosage experience follow-up high risk markov model novel novel strategies patient oriented prevent programs randomized trial tool transplant database

Acute African American Allografting Car Phone Caucasians Cessation of life Characteristics Clinical Communication Tools Comorbidity Data Data Linkages Data Set Databases Decision Making Diabetes Mellitus Dialysis procedure Dose Drug Combinations Environment Equilibrium Evaluation Event Food and Drug Administration Drug Approval Graft Survival Health Immunologics Immunosuppression Immunosuppressive Agents Incidence Infection Institutes Internet Kidney Failure Kidney Transplantation Lead Link Lymphoma Maintenance Malignant Neoplasms Measures Medical Medicare Medicare claim Modeling Morbidity - disease rate Mycophenolate Organ Organ Donor Organ Procurements Organ Transplantation Outcome Outcomes Research Patient risk Patients Pharmaceutical Preparations Pharmacy facility Physicians Pneumonia Pregnancy Probability Procedures Protocols documentation Race Randomized Controlled Trials Regimen Registries Relative (related person)Reporting Research Resources Risk Safety Sepsis Specialist Staging Subgroup Survival Rate Tacrolimus Time Toxic effect Transplant Recipients Transplantation Update Urinary tract infection Weight base blind cohort cost cost effective cost effectiveness data registry design dosage experience follow-up high risk markov model novel novel strategies patient oriented prevent programs randomized trial tool transplant database

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项目摘要

DESCRIPTION (provided by applicant): Kidney transplant (KTx) professionals have many choices of immunosuppressive (IS) medications and regimens for their patients. With early acute rejection (AR) rates now low and short term graft survival high, individualized long-term graft survival depends on patients' underlying co-morbidities or complications of IS medications. Yet few studies or data exist on how to balance the trade-offs between IS efficacy (in preventing AR) versus complications, including infections, cancers and new onset diabetes after transplant (NODAT). Randomized trials or FDA-sanctioned Risk Evaluation and Mitigation Strategies help with very specific situations; but along with prior analyses of large national databases, also have many limitations. In this study, we propose to use a novel, three-database linkage of the a) U.S.A. national Organ Procurement and Transplant Network (OPTN) registry: recording initial data on all KTx and subsequent survival outcomes, b) a Medicare billing claims database: covers the first 3 years post-KTx, and c) a national Pharmacy Clearinghouse Database (PCD) that covers 60% of all medication fills in the U.S.A. Using this integration, we can minimize limitations of prior approaches to develop accurate, longitudinal, national level data on the transplant procedures, IS use, survival and non-fatal morbidity. Our investigative team of KTx specialists, economists and statisticians, all with transplant database and outcomes research expertise, can then assess in a more rigorous way than previously possible, the efficacy and morbidity tradeoffs of the IS regimens and doses. In the proposed CISTEM study (Choosing Immune Suppression in Renal Transplantation by Efficacy and Morbidity), we will complete the following three aims: 1) To construct a novel linkage of data from the OPTN registry, an updated Medicare claims dataset and the PCD to quantify the associations of KTx IS with outcome metrics of efficacy and morbidity, adjusted for demographic, medical and immunologic parameters; through propensity-score and covariate-adjusted survival models that will quantify the association between IS regimen or dose and specific measures of efficacy (AR) or morbidity (major infections, cancers, NODAT) that contribute to the hard outcomes of graft survival and patient survival, with sub-analyses for key racial and high-risk subgroups; 2) To use the transition probabilities of events, generated in aim 1, to develop Markov models and calculate the overall cost-effectiveness, including trade-off costs, for each of the major IS regimens in use, by overall group and in the key sub-groups mentioned above; and 3) To use the decision analytics from Aims 1 and 2 to generate individualized and real-time reports of the predicted efficacy/complications outcomes and costs of different KTx IS regimens through a free and updateable patient-focused web- or mobile phone-based risk engine and communication tool. The long-term significance is that physicians and patients will be able to make IS choices in a more cost-effective and better informed manner than any other strategy currently available.

描述（由申请人提供）：肾脏移植（KTX）专业人员有许多选择对患者的免疫抑制（IS）药物和方案。由于早期急性排斥（AR）率现在低和短期移植物存活较高，个性化的长期移植物存活取决于患者的基本合并症或IS药物并发症。然而，关于如何在移植后（NODAT）之后的感染，癌症和新的发作糖尿病（NODAT）之间的并发症与并发症（包括感染，癌症和新发作糖尿病（NODAT））之间的并发症，几乎没有研究或数据。随机试验或FDA批准的风险评估和缓解策略有助于在非常具体的情况下；但是，除了对大型国家数据库的先前分析，还许多局限性。在这项研究中，我们建议使用A）A）美国国家器官采购和移植网络（OPTN）注册表的新颖的三atabase链接：记录所有KTX和随后的生存结果的初始数据，b）Medicare账单数据库索赔数据库：涵盖了全国后3年的数据，涵盖了全国性的PROCE填充（PCD）。美国使用这种整合，我们可以最大程度地降低先前方法的局限性，以开发有关移植程序的准确，纵向，国家级别的数据，是使用，生存和非致命性发病率。我们的KTX专家，经济学家和统计学家的调查团队都具有移植数据库和成果研究专业知识，然后可以比以前更严格的方式评估IS方案和剂量的功效和发病率折衷。在拟议的CISTEM研究（通过功效和发病率选择肾脏移植中的免疫抑制），我们将完成以下三个目的：1）构建从OPTN注册表中构建数据的新链接，更新的Medicare索赔数据集和PCD的PCD以量化KTX的关联，以量化有效性和敏感性，调整型号，并调整了敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，敏感性，差异性，敏感性，敏感性，敏感性，敏感性，差异为差异，以降级为单位。通过将量化的倾向评分评分和协变量的生存模型，这些模型将量化IS疗法或剂量之间的关联以及功效（AR）或发病率（主要感染，癌症，癌症，NODAT）的特定量度，这些效果有助于GRAFT存活和患者生存的艰难效果，并具有钥匙范围的kee racial and kee cookial and High-nalalyses and High-r-Risk Subsgrys和高级子群； 2）使用AIM 1中产生的事件的过渡概率来开发马尔可夫模型，并计算每个主要的疗程，包括在使用方案，整个组以及上述关键子组中，包括权衡的成本（包括权衡成本）； 3）使用目标1和2的决策分析来生成有关预测的疗效/并发症结果和不同KTX的成本的个性化和实时报告，是通过免费且可更新的基于患者的Web或基于手机的风险发动机和通信工具的方案。长期的意义是，医生和患者将能够做出比目前可用的任何其他策略更具成本效益，更明智的方式的选择。